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Today, concrete is the most widely used construction material in the world, cement is major component of concrete. Consuming energy in cement industry is very high and CO2 emissions generated during the production of Portland cement has serious environmental threatens. Therefore utilize of pozzolanic material as a supplementary cementitious material has a direct relationship with sustainable development. In this investigation, 2% Nano Silica and 5, 8 and 10% Micro Zeolite (by weight percent) replaced Portland cement constitutes and standard cylindrical specimens were prepared from the mixture. Two types of concrete mixture with water to cementitious material ratio (W/(C + P)) of 0.45 and 0.4 were prepared and they were tested after aging for 7, 28 and 90 days. The effect of these additives on mechanical properties (compressive and tensile strength) and durability were investigated by Electrical Resistivity (ER) and Rapid Chloride Penetration Test (RCPT) at the ages 28 and 90 days. Scanning Electron Microscopy (SEM) and X-Ray Diffraction (XRD) revealed that nano particles could improve quality of concrete. As a result of the tests, increase of mechanical characteristics is not considerable but make significant decrease in penetration of chloride ion and increase electrical resistivity that are appropriate option for controlling of corrosion in reinforced concrete structures. [ABSTRACT FROM AUTHOR]

Administration of high-concentrated suspension formulations (i.e., solid particles dispersed in a liquid vehicle) can be limited due to their greater propensity for needle occlusion. The physical interaction between the solid phase (i.e., particles), the vehicle (i.e., flow field), and injection devices could result in the formation of particle bridging or filtering, posing a major risk in dose delivery accuracy and injectability. Here, given the limited understanding on how clogging initiates in syringe and needle delivery systems, we report an experimental approach to fully characterize the transient injection behavior of suspensions. In particular, we first established a custom fluorescence tagging and imaging technique with integrated force sensor to enable visual observation of local particle concentrations and plunger force monitoring throughout injection. Then, we investigated the effects of key formulation properties and device parameters including particle concentration and morphology, carrier viscosity, injection rate, needle and syringe sizes, and tissue backpressure on the incidence of suspension particle jamming and needle clogging. We performed systematic benchmark studies demonstrating that increasing needle inner diameter (ID) and particle density considerably reduced clogging risk, while increasing vehicle viscosity, particle size, and tissue backpressure significantly increased clogging. The experimental framework presented is amenable to quantifying clogging risk in drug-loaded particle suspensions and provides a guideline to make informed decisions on the tradeoffs between creating particles for pharmaceutical impact and feasibility of injection delivery., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Purpose: Acoustic streaming induced by applying transcranial focused ultrasound (FUS) promotes localized advective solute transport in the brain and has recently garnered research interest for drug delivery and enhancement of brain waste clearance. The acoustic streaming behavior in brain tissue is difficult to model numerically and thus warrants an in vitro examination of the effects of using different sonication parameters, in terms of frequency, intensity, and pulse duration (PD)., Methods: Melamine and polyvinyl alcohol (PVA) foams were used to mimic the porous brain tissue, which contains leptomeningeal fenestrations and perivascular space, while agar hydrogel was used to emulate denser neuropil. FUS was delivered to these media, which were immersed in a phosphate-buffered saline containing toluidine blue O dye, across various frequencies (400, 500, and 600 kHz; applicable to transcranial delivery) in a pulsed mode at two different spatialpeak pulse-average intensities (3 and 4 W/cm2)., Results: Image analysis showed that the use of 400 kHz yielded the greatest dye infiltration in melamine foam, while sonication had no impact on infiltration in the agar hydrogel due to the dominance of diffusional transport. Using a fixed spatial-peak temporal-average intensity of 0.4 W/cm2 at 400 kHz, a PD of 75 ms resulted in the greatest infiltration depth in both melamine and PVA foams among the tested range (50-150 ms)., Conclusion: These findings suggest the existence of a specific frequency and PD that induce greater enhancement of solute/fluid movement, which may contribute to eventual in vivo applications in promoting waste clearance from the brain.

Multiple sclerosis (MS), a chronic neurodegenerative disease driven by damage to the protective myelin sheath, is currently incurable. Today, all clinically available treatments modulate the immune-mediated symptoms of the disease but they fail to stop neurodegeneration in many patients. Remyelination, the regenerative process of myelin repair by oligodendrocytes, which is considered a necessary step to protect demyelinated axons and stop neuronal death, is impaired in MS patients. One of the major obstacles to finding effective remyelinating drugs is the lack of biomimetic drug screening platforms that enable quantification of compounds' potential to stimulate 3D myelination in the physiologically relevant axon-like environment. To address this need, we built a unique myelination drug discovery platform, by expanding our previously developed technology, artificial axons (AAs), which enables 3D-printing of synthetic axon mimics with the geometry and mechanical properties closely resembling those of biological axons. This platform allows for high-throughput phenotypic myelination assay based on quantification of 3D wrapping of myelin membrane around axons in response to compounds. Here, we demonstrate quantification of 3D myelin wrapping by rat oligodendrocytes around the axon mimics in response to a small library of known pro-myelinating compounds. This assay shows pro-myelinating activity for all tested compounds consistent with the published in vitro and in vivo data, demonstrating predictive power of AA platform. We find that stimulation of myelin wrapping by these compounds is dose-dependent, providing a facile means to quantify the compounds' potency and efficacy in promoting myelin wrapping. Further, the ranking of relative efficacy among these compounds differs in this 3D axon-like environment as compared to a traditional oligodendrocyte 2D differentiation assay quantifying area of deposited myelin membrane. Together, we demonstrate that the artificial axons platform and associated phenotypic myelin wrapping assay afford direct evaluation of myelin wrapping by oligodendrocytes in response to soluble compounds in an axon-like environment, providing a predictive tool for the discovery of remyelinating therapies., (© 2023. The Author(s).)

Objectives: Tertiary and quaternary (TQ) care refers to complex cases requiring highly specialized health services. Our study aimed to compare the ability of a natural language processing (NLP) model to an existing human workflow in predictively identifying TQ cases for transfer requests to an academic health center., Materials and Methods: Data on interhospital transfers were queried from the electronic health record for the 6-month period from July 1, 2020 to December 31, 2020. The NLP model was allowed to generate predictions on the same cases as the human predictive workflow during the study period. These predictions were then retrospectively compared to the true TQ outcomes., Results: There were 1895 transfer cases labeled by both the human predictive workflow and the NLP model, all of which had retrospective confirmation of the true TQ label. The NLP model receiver operating characteristic curve had an area under the curve of 0.91. Using a model probability threshold of ≥0.3 to be considered TQ positive, accuracy was 81.5% for the NLP model versus 80.3% for the human predictions ( P  =   .198) while sensitivity was 83.6% versus 67.7% ( P <.001)., Discussion: The NLP model was as accurate as the human workflow but significantly more sensitive. This translated to 15.9% more TQ cases identified by the NLP model., Conclusion: Integrating an NLP model into existing workflows as automated decision support could translate to more TQ cases identified at the onset of the transfer process., Competing Interests: None declared., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Transport of interstitial fluid and solutes plays a critical role in clearing metabolic waste from the brain. Transcranial application of focused ultrasound (FUS) has been shown to promote localized cerebrospinal fluid solute uptake into the brain parenchyma; however, its effects on the transport and clearance of interstitial solutes remain unknown. We demonstrate that pulsed application of low-intensity FUS to the rat brain enhances the transport of intracortically injected fluorescent tracers (ovalbumin and high molecular-weight dextran), yielding greater parenchymal tracer volume distribution compared to the unsonicated control group (ovalbumin by 40.1% and dextran by 34.6%). Furthermore, FUS promoted the drainage of injected interstitial ovalbumin to both superficial and deep cervical lymph nodes (cLNs) ipsilateral to sonication, with 78.3% higher drainage observed in the superficial cLNs compared to the non-sonicated hemisphere. The application of FUS increased the level of solute transport visible from the dorsal brain surface, with ~ 43% greater area and ~ 19% higher fluorescence intensity than the unsonicated group, especially in the pial surface ipsilateral to sonication. The sonication did not elicit tissue-level neuronal excitation, measured by an electroencephalogram, nor did it alter the molecular weight of the tracers. These findings suggest that nonthermal transcranial FUS can enhance advective transport of interstitial solutes and their subsequent removal in a completely non-invasive fashion, offering its potential non-pharmacological utility in facilitating clearance of waste from the brain., (© 2023. The Author(s).)

Low-intensity transcranial focused ultrasound (tFUS) offers new functional neuromodulation opportunities, enabling stimulation of cortical as well as deep brain areas with high spatial resolution. Brain stimulation of awake sheep, in the absence of the confounding effects of anesthesia on brain function, provides translational insight into potential human applications with safety information supplemented by histological analyses. We examined the effects of tFUS pulsing parameters, particularly regarding pulse durations (PDs), on stimulating the cortical motor area (M1) and its thalamic projection in unanesthetized, awake sheep (n = 8). A wearable tFUS headgear, custom-made for individual sheep, enabled experiments to be conducted without using anesthesia. FUS stimuli, each 200 ms long, were delivered to the M1 and the thalamus using three different PDs (0.5, 1, and 2 ms) with the pulse repetition frequency (PRF) adjusted to maintain a 70% duty cycle at a derated in situ spatial-peak temporal-average intensity (Ispta) of 3.6 W/cm2. Efferent electromyography (EMG) responses to stimulation were quantified from both hind limbs. Group-averaged EMG responses from each of the hind limbs across the experimental conditions revealed selective responses from the hind limb contralateral to sonication. The use of 0.5 and 1 ms PDs generated higher EMG signal amplitudes compared to those obtained using a 2 ms PD. Faster efferent response was also observed from thalamic stimulation than that from stimulating the M1. Post-sonication behavioral observation and histological assessment performed 24 h and 1 month after sonication were not indicative of any abnormalities. The results suggest the presence of pulsing scheme-dependent effects of tFUS on brain stimulation and attest its safety in awake large animals., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Low-intensity transcranial focused ultrasound (FUS) has gained momentum as a non-/minimally-invasive modality that facilitates the delivery of various pharmaceutical agents to the brain. With the additional ability to modulate regional brain tissue excitability, FUS is anticipated to confer potential neurotherapeutic applications whereby a deeper insight of its safety is warranted. We investigated the effects of FUS applied to the rat brain (Sprague-Dawley) shortly after an intracortical injection of fluorescent interstitial solutes, a widely used convection-enhanced delivery technique that directly (i.e., bypassing the blood-brain-barrier (BBB)) introduces drugs or interstitial tracers to the brain parenchyma. Texas Red ovalbumin (OA) and fluorescein isothiocyanate-dextran (FITC-d) were used as the interstitial tracers. Rats that did not receive sonication showed an expected interstitial distribution of OA and FITC-d around the injection site, with a wider volume distribution of OA (21.8 ± 4.0 µL) compared to that of FITC-d (7.8 ± 2.7 µL). Remarkably, nearly half of the rats exposed to the FUS developed intracerebral hemorrhaging (ICH), with a significantly higher volume of bleeding compared to a minor red blood cell extravasation from the animals that were not exposed to sonication. This finding suggests that the local cerebrovascular injury inflicted by the micro-injection was further exacerbated by the application of sonication, particularly during the acute stage of injury. Smaller tracer volume distributions and weaker fluorescent intensities, compared to the unsonicated animals, were observed for the sonicated rats that did not manifest hemorrhaging, which may indicate an enhanced degree of clearance of the injected tracers. Our results call for careful safety precautions when ultrasound sonication is desired among groups under elevated risks associated with a weakened or damaged vascular integrity.

Efficient transport of solutes in the cerebrospinal fluid (CSF) plays a critical role in their clearance from the brain. Convective bulk flow of solutes in the CSF in the perivascular space (PVS) is considered one of the important mechanisms behind solute movement in the brain, before their ultimate drainage to the systemic lymphatic system. Acoustic pressure waves can impose radiation force on a medium in its path, inducing localized and directional fluidic flow, known as acoustic streaming. We transcranially applied low-intensity focused ultrasound (FUS) to rats that received an intracisternal injection of fluorescent CSF tracers (dextran and ovalbumin, having two different molecular weights-M w ). The sonication pulsing parameter was determined on the set that propelled the aqueous solution of toluidine blue O dye into a porous media (melamine foam) at the highest level of infiltration. Fluorescence imaging of the brain showed that application of FUS increased the uptake of ovalbumin at the sonicated plane, particularly around the ventricles, whereas the uptake of high-M w dextran was unaffected. Numerical simulation showed that the effects of sonication were non-thermal. Sonication did not alter the animals' behavior or disrupt the blood-brain barrier (BBB) while yielding normal brain histology. The results suggest that FUS may serve as a new non-invasive means to promote interstitial CSF solute transport in a region-specific manner without disrupting the BBB, providing potential for enhanced clearance of waste products from the brain., (© 2022. The Author(s).)

Background: Shareable e-scooters have become popular, but injuries to riders and bystanders have not been well characterized. The goal of this study was to describe e-scooter injuries and estimate the rate of injury per e-scooter trip., Methods and Findings: Retrospective review of patients presenting to 180 clinics and 2 hospitals in greater Los Angeles between January 1, 2014 and May 14, 2020. Injuries were identified using a natural language processing (NLP) algorithm not previously used to identify injuries, tallied, and described along with required healthcare resources. We combine these tallies with municipal data on scooter use to report a monthly utilization-corrected rate of e-scooter injuries. We searched 36 million clinical notes. Our NLP algorithm correctly classified 92% of notes in the testing set compared with the gold standard of investigator review. In total, we identified 1,354 people injured by e-scooters; 30% were seen in more than one clinical setting (e.g., emergency department and a follow-up outpatient visit), 29% required advanced imaging, 6% required inpatient admission, and 2 died. We estimate 115 injuries per million e-scooter trips were treated in our health system., Conclusions: Our observed e-scooter injury rate is likely an underestimate, but is similar to that previously reported for motorcycles. However, the comparative severity of injuries is unknown. Our methodology may prove useful to study other clinical conditions not identifiable by existing diagnostic systems., Competing Interests: The authors have declared that no competing interests exist.

Purpose: The purpose of this study was to evaluate if transcutaneous application of low-intensity ultrasound can locally enhance the effects of finasteride on hair growth in a murine model of androgenic alopecia (AA)., Methods: AA mice (injected twice per week with testosterone enanthate, n=11), under daily oral administration of finasteride, received 1-MHz ultrasound for 1 hour at the unilateral thigh area five times per week for 5 weeks. Non-thermal and non-cavitational ultrasound was delivered in a pulsed manner (55-ms pulse duration with a repetition frequency of 4 Hz). Skin temperature was measured during sonication, and the measurements were validated with numerical simulations of sonication-induced tissue temperature changes. Hair growth was assessed both photographically and histologically., Results: We found more hair growth on the sonicated thigh area than on the unsonicated thigh, beginning from week 3 through the end of the experiment. Histological analyses showed that the number of hair follicles doubled in the skin sections that received sonication compared to the unsonicated zone, with thicker follicular diameter and skin. An over five-fold increase was also observed in the anagen/telogen ratio in the sonicated area, suggesting an enhanced anagen phase. Skin temperature was unaltered by the administered sonication., Conclusion: The findings of the present study suggest that pulsed application of ultrasound promotes hair growth, potentially by disrupting the binding of albumin to finasteride. This may suggest further applications to enhance the pharmacological effects of other relevant drugs exhibiting high plasma protein binding.

To address current unmet needs in terms of scalability and material biocompatibility for future photocrosslinking-based additive manufacturing technologies, emergent platform designs are in inexorable demand. In particular, a shift from the present use of cell-damaging UV light sources in light-based three-dimensional (3D) bioprinting methods demands new platforms. We adopted an organic light-emitting diode (OLED) microdisplay as a digital visible light modulator to create a 3D printing platform modality that offers scalability and multi-material capability while forgoing the need for UV photocrosslinking. We formulate biocompatible inks that are visible light-crosslinkable with relatively quick photoinitiation rates. We demonstrated successful attachment and rapid growth of primary human dermal fibroblast-adult (HDF-a) cells on biological substrates fabricated using the OLED platform. This platform incites new possibilities by providing a simple-yet-effective means for low-cost, high-throughput, and multi-material 3D fabrication of functional structures made of polymers, ceramic composites, and biomaterials., Competing Interests: The authors declare no competing interests., (© 2021 The Authors.)

Transcranial application of pulsed low-intensity focused ultrasound (FUS) modulates the excitability of region-specific brain areas, and anesthetic confounders on brain activity warrant the evaluation of the technique in awake animals. We examined the neuromodulatory effects of FUS in unanesthetized sheep by developing a custom-fit headgear capable of reproducibly placing an acoustic focus on the unilateral motor cortex (M1) and corresponding thalamic area. The efferent responses to sonication, based on the acoustic parameters previously identified in anesthetized sheep, were measured using electromyography (EMG) from both hind limbs across three experimental conditions: on-target sonication, off-target sonication, and without sonication. Excitatory sonication yielded greater amplitude of EMG signals obtained from the hind limb contralateral to sonication than that from the ipsilateral limb. Spurious appearance of motion-related EMG signals limited the amount of analyzed data (~ 10% selection of acquired data) during excitatory sonication, and the averaged EMG response rates elicited by the M1 and thalamic stimulations were 7.5 ± 1.4% and 6.7 ± 1.5%, respectively. Suppressive sonication, while sheep walked on the treadmill, temporarily reduced the EMG amplitude from the limb contralateral to sonication. No significant change was found in the EMG amplitudes during the off-target sonication. Behavioral observation throughout the study and histological analysis showed no sign of brain tissue damage caused by the acoustic stimulation. Marginal response rates observed during excitatory sonication call for technical refinement to reduce motion artifacts during EMG acquisitions as well as acoustic aberration correction schemes to improve spatial accuracy of sonication. Yet, our results indicate that low-intensity FUS modulated the excitability of regional brain tissues reversibly and safely in awake sheep, supporting its potential in theragnostic applications., (© 2021. The Author(s).)

Objectives: Striking histopathological overlap between distinct but related conditions poses a disease diagnostic challenge. There is a major clinical need to develop computational methods enabling clinicians to translate heterogeneous biomedical images into accurate and quantitative diagnostics. This need is particularly salient with small bowel enteropathies; environmental enteropathy (EE) and celiac disease (CD). We built upon our preliminary analysis by developing an artificial intelligence (AI)-based image analysis platform utilizing deep learning convolutional neural networks (CNNs) for these enteropathies., Methods: Data for the secondary analysis was obtained from three primary studies at different sites. The image analysis platform for EE and CD was developed using CNNs including one with multizoom architecture. Gradient-weighted class activation mappings (Grad-CAMs) were used to visualize the models' decision-making process for classifying each disease. A team of medical experts simultaneously reviewed the stain color normalized images done for bias reduction and Grad-CAMs to confirm structural preservation and biomedical relevance, respectively., Results: Four hundred and sixty-one high-resolution biopsy images from 150 children were acquired. Median age (interquartile range) was 37.5 (19.0-121.5) months with a roughly equal sex distribution; 77 males (51.3%). ResNet50 and shallow CNN demonstrated 98% and 96% case-detection accuracy, respectively, which increased to 98.3% with an ensemble. Grad-CAMs demonstrated models' ability to learn different microscopic morphological features for EE, CD, and controls., Conclusions: Our AI-based image analysis platform demonstrated high classification accuracy for small bowel enteropathies which was capable of identifying biologically relevant microscopic features and emulating human pathologist decision-making process. Grad-CAMs illuminated the otherwise "black box" of deep learning in medicine, allowing for increased physician confidence in adopting these new technologies in clinical practice., Competing Interests: The authors report no conflicts of interest., (Copyright © 2021 by European Society for Pediatric Gastroenterology, Hepatology, and Nutrition and North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition.)

Emerging 3D printing technologies offer an exciting opportunity to create customized 3D objects additively from a digital design file. 3D printing may be further leveraged for personalized medicine, clinical trial, and controlled release applications. A wide variety of 3D printing methods exists, and many studies focus on extrusion-based 3D printing techniques that closely resemble hot melt extrusion. In this paper, we explore different pharmaceutical-grade feedstock materials for creating tablet-like dosage forms using a binder jet 3D printing method. In this method, pharmaceutical-grade powders are repeatedly spread onto a build plate, followed by inkjet printing a liquid binder to selectively bind the powders in a predetermined pattern. The physical properties of the pharmaceutical-grade powders and binders have been characterized and a molding method has been developed to select appropriate powder and binder materials for subsequent printing experiments. There was a correlation between the breaking forces of the molded and printed samples, but no clear correlation was observed for disintegration time, which was primarily controlled by the higher porosity of the printed samples. The breaking force and disintegration properties of as-printed and post-processed samples containing indomethacin as an active pharmaceutical ingredient have been measured and compared with relevant literature data., (Copyright © 2020 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.)

Image classification is central to the big data revolution in medicine. Improved information processing methods for diagnosis and classification of digital medical images have shown to be successful via deep learning approaches. As this field is explored, there are limitations to the performance of traditional supervised classifiers. This paper outlines an approach that is different from the current medical image classification tasks that view the issue as multi-class classification. We performed a hierarchical classification using our Hierarchical Medical Image classification (HMIC) approach. HMIC uses stacks of deep learning models to give particular comprehension at each level of the clinical picture hierarchy. For testing our performance, we use biopsy of the small bowel images that contain three categories in the parent level (Celiac Disease, Environmental Enteropathy, and histologically normal controls). For the child level, Celiac Disease Severity is classified into 4 classes (I, IIIa, IIIb, and IIIC)., Competing Interests: Conflicts of Interest: The authors declare no conflict of interest. The funding sponsors had no role in the design of the study; in the collection, analyses or interpretation of data; in the writing of the manuscript; nor in the decision to publish the results.

Celiac Disease (CD) and Environmental Enteropathy (EE) are common causes of malnutrition and adversely impact normal childhood development. CD is an autoimmune disorder that is prevalent worldwide and is caused by an increased sensitivity to gluten. Gluten exposure destructs the small intestinal epithelial barrier, resulting in nutrient mal-absorption and childhood under-nutrition. EE also results in barrier dysfunction but is thought to be caused by an increased vulnerability to infections. EE has been implicated as the predominant cause of under-nutrition, oral vaccine failure, and impaired cognitive development in low-and-middle-income countries. Both conditions require a tissue biopsy for diagnosis, and a major challenge of interpreting clinical biopsy images to differentiate between these gastrointestinal diseases is striking histopathologic overlap between them. In the current study, we propose a convolutional neural network (CNN) to classify duodenal biopsy images from subjects with CD, EE, and healthy controls. We evaluated the performance of our proposed model using a large cohort containing 1000 biopsy images. Our evaluations show that the proposed model achieves an area under ROC of 0.99, 1.00, and 0.97 for CD, EE, and healthy controls, respectively. These results demonstrate the discriminative power of the proposed model in duodenal biopsies classification.

Celiac Disease (CD) is a chronic autoimmune disease that affects the small intestine in genetically predisposed children and adults. Gluten exposure triggers an inflammatory cascade which leads to compromised intestinal barrier function. If this enteropathy is unrecognized, this can lead to anemia, decreased bone density, and, in longstanding cases, intestinal cancer. The prevalence of the disorder is 1% in the United States. An intestinal (duodenal) biopsy is considered the "gold standard" for diagnosis. The mild CD might go unnoticed due to non-specific clinical symptoms or mild histologic features. In our current work, we trained a model based on deep residual networks to diagnose CD severity using a histological scoring system called the modified Marsh score. The proposed model was evaluated using an independent set of 120 whole slide images from 15 CD patients and achieved an AUC greater than 0.96 in all classes. These results demonstrate the diagnostic power of the proposed model for CD severity classification using histological images.

A microlens array has become an important micro-optics device in various applications. Compared with traditional manufacturing approaches, digital light processing (DLP)-based printing enables fabrication of complex three-dimensional (3D) geometries and is a possible manufacturing approach for microlens arrays. However, the nature of 3D printing objects by stacking successive 2D patterns formed by discrete pixels leads to coarse surface roughness and makes DLP-based printing unsuccessful in fabricating optical components. Here, we report an oscillation-assisted DLP-based printing approach for fabrication of microlens arrays. An optically smooth surface (about 1 nm surface roughness) is achieved by mechanical oscillation that eliminates the jagged surface formed by discrete pixels, and a 1-3 s single grayscale ultraviolet (UV) exposure that removes the staircase effect. Moreover, computationally designed grayscale UV patterns allow us to fabricate microlenses with various profiles. The proposed approach paves a way to 3D print optical components with high quality, fast speed, and vast flexibility.

We report a method to prepare highly stretchable and UV curable hydrogels for high resolution DLP based 3D printing. Hydrogel solutions were prepared by mixing self-developed high-efficiency water-soluble TPO nanoparticles as the photoinitiator with an acrylamide-PEGDA (AP) based hydrogel precursor. The TPO nanoparticles make AP hydrogels UV curable, and thus compatible with the DLP based 3D printing technology for the fabrication of complex hydrogel 3D structures with high-resolution and high-fidelity (up to 7 μm). The AP hydrogel system ensures high stretchability, and the printed hydrogel sample can be stretched by more than 1300%, which is the most stretchable 3D printed hydrogel. The printed stretchable hydrogels show an excellent biocompatibility, which allows us to directly 3D print biostructures and tissues. The great optical clarity of the AP hydrogels offers the possibility of 3D printing contact lenses. More importantly, the AP hydrogels are capable of forming strong interfacial bonding with commercial 3D printing elastomers, which allows us to directly 3D print hydrogel-elastomer hybrid structures such as a flexible electronic board with a conductive hydrogel circuit printed on an elastomer matrix.

Among all three-dimensional (3D) printing materials, thermosetting photopolymers claim almost half of the market, and have been widely used in various fields owing to their superior mechanical stability at high temperatures, excellent chemical resistance as well as good compatibility with high-resolution 3D printing technologies. However, once these thermosetting photopolymers form 3D parts through photopolymerization, the covalent networks are permanent and cannot be reprocessed, i.e., reshaped, repaired, or recycled. Here, we report a two-step polymerization strategy to develop 3D printing reprocessable thermosets (3DPRTs) that allow users to reform a printed 3D structure into a new arbitrary shape, repair a broken part by simply 3D printing new material on the damaged site, and recycle unwanted printed parts so the material can be reused for other applications. These 3DPRTs provide a practical solution to address environmental challenges associated with the rapid increase in consumption of 3D printing materials.

Suicide is the second leading cause of death among young adults but the challenges of preventing suicide are significant because the signs often seem invisible. Research has shown that clinicians are not able to reliably predict when someone is at greatest risk. In this paper, we describe the design, collection, and analysis of text messages from individuals with a history of suicidal thoughts and behaviors to build a model to identify periods of suicidality (i.e., suicidal ideation and non-fatal suicide attempts). By reconstructing the timeline of recent suicidal behaviors through a retrospective clinical interview, this study utilizes a prospective research design to understand if text communications can predict periods of suicidality versus depression. Identifying subtle clues in communication indicating when someone is at heightened risk of a suicide attempt may allow for more effective prevention of suicide.

We introduce RNA2DNAlign, a computational framework for quantitative assessment of allele counts across paired RNA and DNA sequencing datasets. RNA2DNAlign is based on quantitation of the relative abundance of variant and reference read counts, followed by binomial tests for genotype and allelic status at SNV positions between compatible sequences. RNA2DNAlign detects positions with differential allele distribution, suggesting asymmetries due to regulatory/structural events. Based on the type of asymmetry, RNA2DNAlign outlines positions likely to be implicated in RNA editing, allele-specific expression or loss, somatic mutagenesis or loss-of-heterozygosity (the first three also in a tumor-specific setting). We applied RNA2DNAlign on 360 matching normal and tumor exomes and transcriptomes from 90 breast cancer patients from TCGA. Under high-confidence settings, RNA2DNAlign identified 2038 distinct SNV sites associated with one of the aforementioned asymetries, the majority of which have not been linked to functionality before. The performance assessment shows very high specificity and sensitivity, due to the corroboration of signals across multiple matching datasets. RNA2DNAlign is freely available from http://github.com/HorvathLab/NGS as a self-contained binary package for 64-bit Linux systems., (© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Rationale: The growing recognition of the importance of splicing, together with rapidly accumulating RNA-sequencing data, demand robust high-throughput approaches, which efficiently analyze experimentally derived whole-transcriptome splice profiles., Results: We have developed a computational approach, called SNPlice, for identifying cis-acting, splice-modulating variants from RNA-seq datasets. SNPlice mines RNA-seq datasets to find reads that span single-nucleotide variant (SNV) loci and nearby splice junctions, assessing the co-occurrence of variants and molecules that remain unspliced at nearby exon-intron boundaries. Hence, SNPlice highlights variants preferentially occurring on intron-containing molecules, possibly resulting from altered splicing. To illustrate co-occurrence of variant nucleotide and exon-intron boundary, allele-specific sequencing was used. SNPlice results are generally consistent with splice-prediction tools, but also indicate splice-modulating elements missed by other algorithms. SNPlice can be applied to identify variants that correlate with unexpected splicing events, and to measure the splice-modulating potential of canonical splice-site SNVs., Availability and Implementation: SNPlice is freely available for download from https://code.google.com/p/snplice/ as a self-contained binary package for 64-bit Linux computers and as python source-code., Contact: pmudvari@gwu.edu or horvatha@gwu.edu, Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Integrative Next Generation Sequencing (NGS) DNA and RNA analyses have very recently become feasible, and the published to date studies have discovered critical disease implicated pathways, and diagnostic and therapeutic targets. A growing number of exomes, genomes and transcriptomes from the same individual are quickly accumulating, providing unique venues for mechanistic and regulatory features analysis, and, at the same time, requiring new exploration strategies. In this study, we have integrated variation and expression information of four NGS datasets from the same individual: normal and tumor breast exomes and transcriptomes. Focusing on SNPcentered variant allelic prevalence, we illustrate analytical algorithms that can be applied to extract or validate potential regulatory elements, such as expression or growth advantage, imprinting, loss of heterozygosity (LOH), somatic changes, and RNA editing. In addition, we point to some critical elements that might bias the output and recommend alternative measures to maximize the confidence of findings. The need for such strategies is especially recognized within the growing appreciation of the concept of systems biology: integrative exploration of genome and transcriptome features reveal mechanistic and regulatory insights that reach far beyond linear addition of the individual datasets.